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Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke

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  • Qin Liu

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    University of Chinese Academy of Sciences, China; Beijing 100049, China)

  • Zhaoping Yang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China)

  • Fang Han

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China)

  • Hui Shi

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China)

  • Zhi Wang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    University of Chinese Academy of Sciences, China; Beijing 100049, China)

  • Xiaodong Chen

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    University of Chinese Academy of Sciences, China; Beijing 100049, China)

Abstract

Ecological environment assessment would be helpful for a rapid and systematic understanding of ecological status and would contribute to formulate appropriate strategies for the sustainability of heritage sites. A procedure based on spatial principle component analysis was employed to measure the ecological status in Bayinbuluke; exploratory spatial data analysis and geo-detector model were introduced to assess the spatio-temporal distribution characteristics and detect the driving factors of the ecological environment. Five results are presented: (1) During 2007–2018, the average values of moisture, greenness, and heat increased by 51.72%, 23.10%, and 4.99% respectively, and the average values of dryness decreased by 56.70%. However, the fluctuation of each indicator increased. (2) The ecological environment of Bayinbuluke was improved from 2007 to 2018, and presented a distribution pattern that the heritage site was better than the buffer zone, and the southeast area was better than the northwest area. (3) The ecological environment presented a significant spatial clustering characteristic, and four types of spatial associations were proposed for assessing spatial dependence among the samples. (4) Elevation, protection partition, temperature, river, road, tourism, precipitation, community resident, and slope were statistically significant with respect to the changes in ecological status, and the interaction of any two factors was higher than the effect of one factor alone. (5) The remote-sensing ecological index (RSEI) could reflect the vegetation growth to a certain extent, but has limited ability to respond to species structure. Overall, the framework presented in this paper realized a visual and measurable approach for a detailed monitoring of the ecological environment and provided valuable information for the protection and management of heritage sites.

Suggested Citation

  • Qin Liu & Zhaoping Yang & Fang Han & Hui Shi & Zhi Wang & Xiaodong Chen, 2019. "Ecological Environment Assessment in World Natural Heritage Site Based on Remote-Sensing Data. A Case Study from the Bayinbuluke," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6385-:d:286626
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    References listed on IDEAS

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    1. Hui Shi & Tiange Shi & Zhaoping Yang & Zhi Wang & Fang Han & Cuirong Wang, 2018. "Effect of Roads on Ecological Corridors Used for Wildlife Movement in a Natural Heritage Site," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    2. Liu, Bing & Huang, Songshan (Sam) & Fu, Hui, 2017. "An application of network analysis on tourist attractions: The case of Xinjiang, China," Tourism Management, Elsevier, vol. 58(C), pages 132-141.
    3. Canale, Rosaria Rita & De Simone, Elina & Di Maio, Amedeo & Parenti, Benedetta, 2019. "UNESCO World Heritage sites and tourism attractiveness: The case of Italian provinces," Land Use Policy, Elsevier, vol. 85(C), pages 114-120.
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    Cited by:

    1. Chao Li & Xuemei Li & Dongliang Luo & Yi He & Fangfang Chen & Bo Zhang & Qiyong Qin, 2021. "Spatiotemporal Pattern of Vegetation Ecology Quality and Its Response to Climate Change between 2000–2017 in China," Sustainability, MDPI, vol. 13(3), pages 1-22, January.
    2. Zhi Wang & Zhaoping Yang & Hui Shi & Fang Han & Qin Liu & Jianwei Qi & Yayan Lu, 2020. "Ecosystem Health Assessment of World Natural Heritage Sites Based on Remote Sensing and Field Sampling Verification: Bayanbulak as Case Study," Sustainability, MDPI, vol. 12(7), pages 1-21, March.
    3. Guoyi Cui & Yan Zhang & Feihang Shi & Wenxia Jia & Bohua Pan & Changkun Han & Zhengze Liu & Min Li & Haohao Zhou, 2022. "Study of Spatiotemporal Changes and Driving Factors of Habitat Quality: A Case Study of the Agro-Pastoral Ecotone in Northern Shaanxi, China," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    4. Yue Chen & Kangning Xiong & Xiaodong Ren & Cai Cheng, 2021. "Vulnerability Comparison between Karst and Non-Karst Nature Reserves—With a Special Reference to Guizhou Province, China," Sustainability, MDPI, vol. 13(5), pages 1-12, February.
    5. Pengwen Gao & Alimujiang Kasimu & Yongyu Zhao & Bing Lin & Jinpeng Chai & Tuersunayi Ruzi & Hemiao Zhao, 2020. "Evaluation of the Temporal and Spatial Changes of Ecological Quality in the Hami Oasis Based on RSEI," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    6. Ning Zhang & Kangning Xiong & Hua Xiao & Juan Zhang & Chuhong Shen, 2023. "Ecological Environment Dynamic Monitoring and Driving Force Analysis of Karst World Heritage Sites Based on Remote-Sensing: A Case Study of Shibing Karst," Land, MDPI, vol. 12(1), pages 1-15, January.

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